Search Results (14,283)

Background and Objectives: Breast cancer is the leading oncological diagnosis among women in Kazakhstan, yet a substantial proportion of cases are still detected beyond the earliest stages, particularly in peripheral regions such as Aktobe. Despite a national mammography screening programme covering women aged 40–70 years since 2018, structural differences in access to early diagnosis—related to geography, socioeconomic circumstances, and the diagnostic pathway—may compromise outcomes. We aimed to identify factors independently associated with early-stage presentation and to characterise the temporal pattern of early-stage presentation without assuming a monotonic trend. Methods and Materials: We conducted a retrospective, population-based analytical study of all confirmed breast cancer cases (ICD-10 C50) registered in the Aktobe regional cancer registry and diagnosed between 1 January 2015 and 31 December 2025 (n = 2232). The outcome was early-stage presentation, defined literally as Stages I–IIa at diagnosis, with Stages IIb–IV as the comparator; this is a stage-at-presentation classification and is not intended to indicate surgical operability or treatment sequence. Multivariable logistic regression estimated adjusted odds ratios (aORs). Two models were used: Model A included age, sex, residence, administrative nationality, employment/social status, and calendar year; Model B additionally included the diagnostic pathway, which may lie on the causal pathway between structural determinants and stage. Calendar year was modelled as a categorical variable, and a complementary phase-based model (2015–2017, 2018–2019, 2020–2022, 2023–2025) was fitted. A residence-by-year interaction; a multinomial sensitivity analysis separating Stages IIb, III, and IV; discrimination (AUC, Brier score); and calibration (Hosmer–Lemeshow test, calibration plot) were also assessed. Results: Of 2232 patients (99.1% female; mean age 57.0 ± 12.5 years), 1323 (59.3%) presented at Stages I–IIa. In Model A, rural residence (aOR 0.77, 95% CI 0.64–0.93; p = 0.006), unemployment relative to employment (aOR 0.69, 95% CI 0.52–0.90; p = 0.007), Russian administrative nationality (aOR 0.64, 95% CI 0.50–0.82; p < 0.001), and other non-Kazakh nationalities (aOR 0.73, 95% CI 0.58–0.94; p = 0.012) were independently associated with lower odds of Stage I–IIa presentation. In Model B, patient-initiated (self-referral) presentation was associated with lower odds relative to clinical examination room detection (aOR 0.46, 95% CI 0.30–0.72; p < 0.001), whereas organised screening was not significantly associated (aOR 1.52, 95% CI 0.95–2.43; p = 0.082). The calendar-year pattern was clearly non-linear (categorical vs. linear year: likelihood-ratio χ² = 76.1, df = 9, p < 0.001): odds of Stage I–IIa presentation peaked in 2018 (aOR 2.49, 95% CI 1.57–3.93 vs. 2015), were lowest in 2022 (aOR 0.64, 95% CI 0.42–0.97), and partially recovered thereafter. In the phase-based model (reference 2015–2017), the aORs were 1.62 (95% CI 1.22–2.15) for 2018–2019, 0.54 (95% CI 0.41–0.69) for 2020–2022, and 0.62 (95% CI 0.46–0.84) for 2023–2025. Model discrimination was limited (AUC 0.648, 95% CI 0.625–0.671; Brier score 0.226) with acceptable calibration (Hosmer–Lemeshow χ² = 8.38, df = 8, p = 0.40). Conclusions: In this registry-based cohort, rural residence, unemployment, non-Kazakh administrative nationality, and patient-initiated presentation were independently associated with lower odds of early-stage breast cancer presentation. The temporal pattern was non-monotonic, with the highest odds around the 2018 screening expansion, a marked reduction during 2020–2022, and only partial recovery thereafter. These are observational associations rather than causal or programme-evaluation findings; they should be interpreted as hypothesis-generating and require confirmation with screening-process, service-capacity, and patient-level access data. Full article

Breast cancer remains one of the most prevalent malignancies affecting women worldwide and continues to be a leading cause of cancer-related morbidity and mortality. Patients may present with either localized or advanced disease, with clinical outcomes increasingly influenced by molecular subtype and genetic profile. This review highlights the key genetic factors involved in breast cancer, current diagnostic and therapeutic strategies, and promising emerging approaches that may shape future clinical management. Breast cancer diagnosis typically involves clinical breast examination, imaging techniques such as mammography and ultrasound, and confirmatory biopsies. Genetic mutations in specific genes are strongly linked to the development, progression, and metastasis of the disease. Treatment options for localized breast cancer continue to include surgery (lumpectomy or mastectomy) and radiotherapy, combined with systemic therapies tailored to tumor biology, such as endocrine therapy, human epidermal growth factor receptor 2 (HER2)-targeted therapy, and cyclin-dependent kinase (CDK)4/6 inhibitors. For advanced or metastatic breast cancer, recent therapeutic advances include the use of immunotherapy (e.g., immune checkpoint inhibitors), Poly (ADP-ribose) polymerase (PARP) inhibitors for Breast Cancer gene (BRCA)-mutated cancers, antibody–drug conjugates, and novel targeted agents, which have significantly improved patient outcomes in selected populations. Recent findings in breast cancer genetics have highlighted the critical role of germline and somatic mutations, particularly in genes such as BRCA1, BRCA2, phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA), and TP53, in driving tumor initiation, progression, and therapeutic response. Molecular profiling and next-generation sequencing technologies have enabled more precise tumor classification and facilitated the development of personalized treatment strategies. Despite these advances, treatment resistance and disease recurrence remain major challenges, particularly in aggressive subtypes such as triple-negative breast cancer. Consequently, ongoing research is exploring alternative and complementary approaches, including nanotechnology-based drug delivery systems, gene editing techniques such as clustered regularly interspaced short palindromic repeats-Cas9 (CRISPR-associated protein 9) (CRISPR-Cas9), cancer vaccines, and the integration of traditional and plant-derived compounds. These strategies aim to enhance therapeutic efficacy, reduce systemic toxicity, and overcome resistance mechanisms. Full article

Obesity is a chronic, relapsing disease and a significant oncological risk factor. The correlation is most pronounced and consistent for endometrial cancer. Conversely, evidence linking obesity to ovarian cancer is less robust and varies by histotype, while the association with cervical cancer is influenced by factors related to screening, diagnosis, treatment, and survival. This review examines obesity, particularly class III (morbid) obesity, in relation to the risk of gynaecological cancer, diagnostic approaches, and management strategies. A structured narrative review of PubMed/MEDLINE, Cochrane Library, Scopus and Web of Science Core Collection was conducted for literature published between January 2000 and December 2025. Eligible evidence included systematic reviews, meta-analyses, cohort and case–control studies, mechanistic studies and clinical guidance relevant to obesity and endometrial, ovarian or cervical cancer. Title/abstract screening and full-text selection were conducted using predefined criteria for conceptual relevance and clinical applicability. Excess adiposity contributes to endometrial carcinogenesis through hormonal dysregulation, insulin resistance and hyperinsulinaemia, adipokine imbalance, chronic inflammation, and oxidative stress. In ovarian cancer, associations are generally weaker but appear more relevant for selected histological subtypes and cumulative adiposity exposure. In cervical cancer, obesity should not be interpreted as replacing HPV-driven pathogenesis; rather, it may affect screening adequacy, treatment selection, perioperative risk, and disease-specific survival in morbidly obese patients. Current evidence does not support morbid obesity as an independent driver of all gynaecological cancers. It supports obesity as a major modifiable risk factor and clinical modifier, particularly for endometrial cancer, and highlights the need for pragmatic risk stratification based on BMI class, adiposity distribution, metabolic comorbidity, functional status and cancer-site-specific pathways. Biomarker evidence remains hypothesis-generating, and obesity-integrated oncological pathways require prospective validation in patients with a BMI ≥ 40 kg/m². Full article

Liquid biopsy has emerged as a transformative approach in modern oncology, offering minimally invasive access to tumor-derived biomarkers through the analysis of circulating tumor DNA, cell-free DNA, and extracellular vesicles such as exosomes. Unlike conventional tissue biopsies, liquid biopsy enables real-time monitoring of tumor dynamics, molecular heterogeneity, treatment response, and the development of therapeutic resistance. Recent advances in ultra-sensitive molecular technologies, including digital droplet polymerase chain reaction, next-generation sequencing, methylation profiling, and fragmentomic analysis, have substantially improved the sensitivity and specificity of circulating nucleic acid detection, facilitating their integration into precision cancer medicine. ctDNA analysis has demonstrated significant clinical utility across multiple malignancies, including lung, breast, colorectal, pancreatic, and prostate cancers, particularly in the identification of actionable genomic alterations, minimal residual disease, and mechanisms of acquired resistance. In parallel, cell-free DNA provides broader insights into tumor biology and systemic genomic alterations, while exosomes contribute additional layers of molecular information through the transport of nucleic acids, proteins, and signaling molecules involved in intercellular communication and tumor microenvironment modulation. The integration of artificial intelligence and machine learning approaches further enhances the interpretative power of liquid biopsy-derived datasets and supports the development of personalized therapeutic strategies. Despite these advances, important challenges remain, including low tumor fraction in early-stage disease, biological and technical variability, clonal hematopoiesis-associated false positives, assay standardization, and cost-effectiveness considerations. Nevertheless, the expanding clinical applicability of liquid biopsy technologies positions them as essential components of contemporary precision oncology. This review summarizes the biological foundations, analytical methodologies, current clinical applications, technological innovations, and future perspectives of circulating tumor DNA, cell-free DNA, and exosome-based liquid biopsies in cancer diagnosis, monitoring, and personalized treatment strategies. Full article

Background: Despite therapeutic advances, many patients with metastatic lung cancer still lack access to comprehensive molecular profiling, often due to inadequate biopsy samples. Percutaneous ultrasound-guided needle aspiration biopsy (US-NAB) from both lung and metastatic sites has shown promise in improving diagnostic and molecular profiling accuracy. However, data regarding its real-world utilization, diagnostic performance, and contribution to comprehensive molecular profiling in unselected patients with advanced lung cancer remain limited. Methods: We performed a secondary (post hoc) analysis of prospectively collected data from the Propheta Pro study, a prospective observational cohort of patients with advanced lung cancer. The aim of the present analysis was to assess patterns of invasive sampling procedures, with a particular focus on the prevalence of US-NAB utilization across histologic subtypes. We also assessed the diagnostic yield of US-NAB for cancer diagnosis, comprehensive genomic profiling, and PD-L1 expression. Results: Among the 348 patients enrolled, 123 (35.3%) underwent US-NAB, making it the most frequently utilized sampling technique overall and across individual histologic subtypes. Biopsy of metastatic sites was significantly more common than primary lung tumors (113, 91.9% versus 10, 8.1%; p < 0.001), with superficial metastases being the primary target (110, 89.4%). US-NAB demonstrated high diagnostic yields: 97% for histological diagnosis, 91.1% for comprehensive genomic profiling, and 95.8% for PD-L1 testing. Only two minor, self-limiting complications were observed. Conclusions: US-NAB is a highly effective yet underrecognized diagnostic option for advanced lung cancer, particularly given the high prevalence of accessible superficial metastases. Integrating US-NAB into interventional pulmonology services could enhance diagnostic and molecular profiling yields. Full article

The prediction of the therapeutic response and of the patient outcome following neoadjuvant chemoradiotherapy (nCRT) in rectal cancer (RC) is still a challenging issue. The role of Annexin 1 (ANXA1) in the modulation of the tumor cells’ growth and metastasis has been recently demonstrated, being associated with aggressive pathological features and poor outcome in specific malignancies. The present study aimed to evaluate the association between ANXA1 expression, survival, and clinicopathological parameters of a group of patients diagnosed with ypT3 locally advanced rectal cancer (LARC) following nCRT. The study group consisted of 60 LARC patients with ypT3 tumor stage showing a tumor fragmentation pattern following nCRT. The clinicopathological characteristics and survival parameters in relation to ANXA1 immunohistochemistry characteristics and its scoring were evaluated. ANXA1 expression in tumor cells showed variable intense luminal membrane or combined luminal membrane and cytoplasmic location, excepting three negative cases. The statistical analysis demonstrated a significant association between high ANXA1 expression and ypN category (p < 0.001), perineural invasion (PnI) (p = 0.002), and lymphovascular invasion (LVI) (p = 0.021). Survival analysis showed that high ANXA1 expression is associated with a reduced overall survival (OS) (p = 0.001), while univariate Cox regression confirmed ANXA1 value as an independent predictor of prognosis (H = 5.922, p = 0.004). Our results support ANXA1 value as a potential biomarker of aggressive tumor behavior and poor prognosis in ypT3 LARC patients, with potential implications in diagnosis stratification, opening the prospective to apply precision oncology strategies. However, further studies are required to certify ANXA1 diagnostic and therapeutic relevance in RC patients. Full article

Background/Objectives: Multilocus Inherited Neoplasia Alleles Syndrome (MINAS) is defined by the presence of germline pathogenic or likely pathogenic variants in two or more distinct cancer susceptibility genes (CSGs) in the same individual. Although carriers may present more complex phenotypes, the clinical and molecular spectrum of MINAS remains poorly characterized, particularly in underrepresented populations. We aim to describe this phenomenon in a cohort of individuals from a Chilean institution. Methods: We retrospectively reviewed individuals evaluated at the Oncogenetic Counseling Unit of Fundación Arturo López Pérez (FALP) between 2020 and 2026 who underwent hereditary cancer multi-gene panel testing. Cases fulfilling MINAS criteria were described. We analyzed the association between MINAS and age at cancer diagnosis or multiple primary cancers, and reviewed reported cases with the same gene combinations. Results: From 1962 individuals tested, 398 harbored a pathogenic or likely pathogenic variant, and 14 fulfilled MINAS criteria, yielding a prevalence of 3.51% among positive cases. Breast cancer was the most common tumor type (76.9%), and ATM and CDKN2A were the most frequently involved genes. MINAS was significantly associated with a younger age at cancer diagnosis, but not with multiple primary cancers. Conclusions: MINAS prevalence in our cohort and the association with a younger diagnosis of cancer was consistent with published series. We identified seven previously unreported gene combinations, and common founder variants shifted the pattern away from predominantly BRCA-associated combinations. Despite the small sample size, this study adds relevant data from an underrepresented Latin American population. Full article

The intricate nature of multi-class histopathological images, combined with pronounced class imbalances, complicates automated breast cancer diagnosis and demands AI models capable of generalizing well beyond often limited training data. To address these challenges, this paper explores the generative modeling capability of a symmetry-driven enhanced auxiliary classifier GAN (LSWACGAN) as an all-in-one, data-efficient framework for breast cancer histopathological image classification. LSWACGAN incorporates the Wasserstein loss with gradient penalty to promote greater training stability by mitigating overfitting and preventing vanishing gradients. Assigning smooth category labels to generated samples further helps alleviate the mode collapse problem. The proposed framework brings together three types of symmetry to improve its reliability: the inherent metric symmetry of the Wasserstein distance, the structural symmetry within the auxiliary classifier GAN, and the architectural symmetry between the generator and discriminator networks. Extensive experiments conducted on the well-known BreakHis dataset, supplemented by a thorough ablation study, demonstrate the framework’s competitive edge in a lower-data regime. For binary classification, LSWACGAN closely matches or slightly outperforms leading benchmarks on most selected evaluation metrics. Conversely, in the multi-class scenario, it emerges as a clear forerunner, consistently producing superior results and maintaining robust performance across varying magnification levels. Full article

Background/Objectives: Prostate cancer (PCa) frequently metastasizes to bone, leading to severe clinical complications and reduced quality of life. Accurate and robust imaging-based characterization of bone lesions is therefore critical for diagnosis and treatment planning. Radiomics has emerged as a powerful tool for extracting quantitative information from medical images; however, classical radiomics features are often affected by inter-scanner variability, segmentation dependence, and limited ability to describe lesions with complex biological heterogeneity. This study aims to introduce a translational graph-based radiomics approach designed to extract novel quantitative descriptors with improved robustness and clinical reliability. Methods: A graph representation was derived from segmented Positron Emission Tomography/Computed Tomography (PET/CT) bone lesions by generating a point cloud followed by Delaunay triangulation to preserve geometric information. Graph signal processing techniques were applied to extract three classes of features: orientation, connectivity, and transform-based descriptors. The dataset included PET/CT scans from 50 PCa patients acquired using two different scanners, comprising 92 bone lesions classified as benign or malignant. Correlation analysis with classical radiomics features was performed to assess information redundancy. Robustness against batch effects and segmentation variability was evaluated. Classification performance was tested using Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) models based on proposed features, classical features, and their combination. Results: The proposed features captured non-redundant information compared to classical radiomics and demonstrated superior robustness to scanner-related batch effects and segmentation variability. In classification tasks, models using the proposed features consistently outperformed those based on classical radiomics. Using LDA, the proposed features achieved a mean balanced accuracy of 69.68% and a mean Area Under the Curve (AUC) of 72.14%. With SVM, they achieved a mean balanced accuracy of 65.16% and a mean AUC of 66.49%, exceeding the performance of classical and combined feature sets. Conclusions: This study presents a translational graph-based radiomics framework that extends beyond conventional methodologies, improving robustness and diagnostic performance. The proposed approach shows promise as an integrative tool for more reliable PET/CT-based characterization of bone lesions in prostate cancer. Full article

Pulmonary nodules are circular or irregular lesions visible on chest computed tomography (CT), and their early detection is critical for lung cancer screening. Deep learning detection algorithms have been widely adopted for pulmonary nodule diagnosis; existing lightweight models suffer from redundant network parameters and low detection accuracy for tiny lesions. To address these limitations, this study proposes an improved detection model based on YOLOv8n. First, Omni-Dimensional Dynamic Convolution (ODConv) replaces static convolution in the backbone to enhance multi-morphology nodule feature extraction. Second, the Convolutional Block Attention Module (CBAM) is embedded at multiple positions of the neck network to suppress background interference from blood vessels and normal lung parenchyma. Third, Complete Intersection over Union (CIoU) loss is substituted by Wise Intersection over Union (W-IoU) to optimize bounding box regression for hard samples with blurred boundaries. Experiments on the LUNA16 dataset show that compared with the original YOLOv8n, the proposed model improves Precision by 6.3%, Recall by 8.6%, mAP50 by 3.4%, and mAP50-95% by 2.7% while maintaining high inference speed. Additional generalization verification on the LIDC-IDRI multi-center dataset further proves the robustness of the proposed lightweight architecture, which achieves balanced accuracy and real-time performance compared with mainstream detection models. Full article

Anisakiasis is caused by ingestion of third-stage larvae (L3) of Anisakis in fish. The last decade has improved our understanding of Anisakis and its clinical manifestations, driven by advancements in high-throughput “omics” techniques and molecular diagnostics. This review summarizes major advancements, focusing on molecular mechanisms underlying its pathogenesis, host–pathogen interactions and novel diagnostic approaches. Taxonomical revisions have refined the Anisakis genus, reclassifying several species into Skrjabinisakis and Peritrachelius. Research has highlighted the critical role of Anisakis extracellular vesicles in modulating host immunity. Significant diagnostic breakthroughs include the use of the IgA/IgG4 ratio and antibody avidity profiling to differentiate gastroallergic anisakiasis from chronic urticaria. Identification of α-Gal epitopes in L3 suggests a novel link to α-Gal syndrome and red meat allergy. Ani s 13 and Ani s 14 have been identified as new major allergens, although Ani s 7 remains the gold standard for serological diagnosis. Modern systems biology is revealing how larvae adapt to their host environments, including thermal stress and glucose availability. Finally, emerging evidence suggests potential links between chronic Anisakis exposure and pathologies like cancer and sepsis. These advancements underscore the necessity of global clinical awareness and the potential for Anisakis-derived molecules as templates for future immunotherapies. Full article

Background/Objectives: Breast cancer (BC) remains the most frequently diagnosed malignancy among women worldwide, and patient outcome is strongly influenced by disease stage at diagnosis. Although imaging-based screening has improved early detection, its performance may be reduced in dense breast tissue and is associated with false-positive findings. In addition, tissue biopsy is invasive and unsuitable for longitudinal disease monitoring. Liquid biopsy (LB) has emerged as a minimally invasive approach for detecting tumor-derived material in peripheral blood. However, early-stage tumors typically exhibit low tumor burden and limited biomarker shedding, generating weak systemic signals that challenge reliable detection. This review examines current and emerging LB biomarkers for early BC detection. Methods: A comprehensive review of recent literature was conducted focusing on circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), extracellular vesicles (EVs), circulating RNAs, proteins, and other blood-based biomarkers associated with early BC. Studies addressing biomarker biology, detection technologies, clinical applications, and methodological limitations were critically evaluated. Results: ctDNA, CTCs, EVs, circulating RNAs, proteins, and additional blood-based biomarkers capture distinct aspects of tumor biology and disease evolution. ctDNA enables the analysis of tumor-specific mutations, methylation patterns, and fragmentation profiles, whereas CTCs provide direct cellular and phenotypic information despite their rarity and marked epithelial–mesenchymal plasticity. EVs offer increased molecular stability and actively participate in tumor progression, immune modulation, and metastatic niche formation. Nevertheless, low biomarker abundance, biological heterogeneity, technical variability, and background biological noise continue to limit analytical performance, particularly in early-stage disease. Current evidence further suggests that no single biomarker consistently provides sufficient sensitivity and specificity for reliable early BC detection. Conclusions: LB represents a promising strategy for non-invasive early BC detection. Future clinical implementation will likely depend on integrated multi-analyte approaches that combine complementary genomic, transcriptomic, proteomic, and cellular information, supported by multi-omics technologies and artificial intelligence-based analytical frameworks. Full article

Background: Head and neck squamous cell carcinoma (HNSCC) remains a major global health challenge due to the lack of effective and non-invasive diagnostic tools, often resulting in late-stage detection of cancer. Small extracellular vesicles (sEVs) have emerged as promising biomarkers for early cancer detection and disease monitoring due to their omnipresence and stability in bodily fluids, such as blood plasma. In addition, cancer-derived sEVs specifically carry cargo reflective of oncogene-derived molecular alterations. In summary, these characteristics position sEVs as a potential platform for non-invasive testing of HNSCC. Methods: Plasma-derived sEVs from HNSCC patients (n = 71) and benign subjects (n = 25) were isolated using size exclusion chromatography. Proteomic profiling via liquid chromatography-tandem mass spectrometry identified potential candidate biomarkers, followed by ELISA validation. Results: Proteomic analyses revealed a significant enrichment of multiple proteins in HNSCC-derived sEVs compared to sEVs derived from non-cancer individuals. The von Willebrand factor (vWF) was significantly higher in HNSCC patient-derived sEVs compared to those derived from benign individuals. A validation cohort confirmed that sEV-associated vWF (sEV-vWF) effectively distinguished HNSCC patients from benign subjects, demonstrating strong diagnostic performance, specifically in laryngeal HNSCC (AUC = 0.82) and oropharyngeal HNSCC (AUC = 0.96) patient cohorts. Moreover, postoperative reductions and recurrence-associated increases in sEV-vWF levels corresponded with clinical outcomes, indicating its potential as a dynamic disease indicator. Conclusions: These findings highlight sEV-vWF as a novel and non-invasive biomarker with potential applications in early detection and real-time monitoring of HNSCC, supporting advancement toward precision liquid biopsy strategies in head and neck oncology. Full article

Background: Tuberculosis (TB) remains a leading cause of global morbidity and mortality, yet its impact extends far beyond microbiological cure. Many TB survivors experience persistent structural lung damage or functional impairment consistent with post-TB lung disease, while growing evidence highlights long-term non-respiratory health outcomes. Synthesizing evidence across lung and non- respiratory health outcomes, along with their risk factors, is critical to inform long-term TB care. Methods: We conducted a scoping review including systematic reviews reporting on post-TB long-term health outcomes. A search was performed in PubMed/MEDLINE on 27 July 2025, using terms related to “tuberculosis,” “systematic review,” “meta-analysis,” “sequelae” and “long-term health outcomes,” without language restrictions. Results: Nine systematic reviews met inclusion criteria. Most focused on pulmonary outcomes and consistently demonstrated that TB is associated with chronic airflow obstruction, reduced lung function, and an increased long-term risk of lung cancer, although residual confounding from environmental, clinical, and socioeconomic factors cannot be excluded. While younger adults are more prone to developing COPD after TB in high TB burden settings, older individuals face a higher risk of broader post-TB lung sequelae. Evidence suggested that TB survivors are at increased risk of non-respiratory complications. HIV co-infection, low CD4 counts, older age, pre-existing hepatitis, prior TB treatment, and hypoalbuminemia were associated with post-TB liver injury, while baseline hearing impairment and HIV co-infection increased the likelihood of post-TB hearing loss. TB was also linked to elevated risk of several non-pulmonary cancers, including oesophageal, cervical, hematological, pancreatic, and gastric malignancies, with the highest risk within the first year after TB diagnosis and persisting, though attenuated, in subsequent years. Conclusion: TB should be viewed as a chronic condition with enduring lung and non-respiratory health outcomes. TB survivors face increased risks of COPD, lung cancer, and a range of non-respiratory health outcomes, including hepatic and auditory complications, particularly among high-risk groups, such as those living with HIV infection, along with baseline hearing and hepatic impairment. Public health programmes must extend care beyond microbiological cure to include integrated, post-TB long-term monitoring of lung, hepatic and hearing across all ages, including malignancy surveillance, after baseline assessments to identify high-risk TB survivors. Future research should also elucidate risk factors for post-TB malignancy, and clarify the relationship between neurological, renal, and musculoskeletal sequelae and TB to inform evidence-based TB survivorship care. Full article